Modern wireless networks face a variety of security threats ranging from unauthorized access and intrusions to sophisticated malware and privacy attacks. Machine Learning (ML) has emerged as a powerful tool to enhance security in these networks by automatically detecting threats, identifying anomalies, strengthening communication protocols, and preserving user privacy. This chapter explores how ML techniques can be applied to wireless network security, balancing theoretical foundations with real-world case studies and practical Python implementations.